Artificial Intelligence & ML Predictions CEO / Admin
Kaltiv integrates 6 machine learning models trained on your real operational data.
Access
ML predictions appear directly in the relevant modules (dashboard, agriculture, sales). No additional configuration is required.
Available Models
| Model | Type | Accuracy | Data | Module |
|---|---|---|---|---|
| Yield prediction | CatBoost (ONNX) | R² = 0.79 | Weather + harvest history | Agriculture |
| Quality prediction | CatBoost | 73.7% | Harvest conditions | Agriculture |
| Palm oil price | LightGBM | Trend | Market + seasonality | Sales |
| Palm nut price | LightGBM | Trend | Market + seasonality | Sales |
| Papaya price | LightGBM | Trend | Market + seasonality | Sales |
| Customer scoring | ML algorithm | Score 0-100 | Order history | CRM |
Yield Predictions
Where: Dashboard → "Predictions" section
The CatBoost model analyses weather data (800+ readings) and harvest history (78 records) to predict:
- Expected yield per plot (kg/hectare)
- Optimal harvest period
- Risk factors (drought, excessive rainfall)
Quality Predictions
Where: Agriculture → Plot detail
Assesses expected harvest quality based on:
- Temperature and humidity over recent days
- Bunch maturity stage
- Plot's historical quality
Price Predictions
Where: Sales & CRM → Analytics
Three LightGBM models provide price forecasts for:
- Palm oil: Price per litre, weekly trend
- Palm nuts: Price per kilogram
- F1 Horizon papaya: Price per kilogram
Intelligent Customer Scoring
Where: Sales & CRM → Customer Scoring (/dashboard/sales-crm/customer-scoring)
The algorithm scores each customer on a scale of 0 to 100 by analysing:
- Order frequency and volume
- Payment regularity
- Length of commercial relationship
- Growth potential
AI Advisor — Digital Chief of Staff
Where: Floating button in the bottom right of each page + Settings > AI Advisor
The Kaltiv AI Advisor uses Claude (Anthropic) with 44 specialised tools organised in 4 layers:
| Layer | Tools | Domain |
|---|---|---|
| L1 — Core | 12 tools | HR, leave, payroll, operations, recommendations |
| L2 — Lean | 15 tools | PDCA, 8D, QRQC, Kanban, SPC, 5S |
| L3 — Knowledge | 7 tools | RAG documents, facts, semantic search |
| L4 — Advisory | 10 tools | ML predictions, memory, scheduled reports, external sources |
Advanced Features
- RAG Knowledge Base: Upload documents (PDF, Excel, text) that are automatically analysed and indexed
- Teaching Mode: Teach business facts that the advisor retains and uses
- Proactive Recommendations: Automatic detection of anomalies, trends and opportunities
- Personalised Memory: The advisor learns your preferences over time
- Scheduled Reports: Daily, weekly or monthly briefings generated automatically
- External Sources: Connect Google Drive and RSS feeds for continuous enrichment
For the full guide, see the AI Advisor page.
Each prediction displays a badge indicating its source: ML (trained model), Heuristic (business rule), or Hybrid (combination of both). Accuracy rates are shown to help you assess reliability.
Quality models require 200+ labelled harvests to reach optimal accuracy (76 available currently). Predictions improve with every new data point recorded.